Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Effects of instructional changes on student learning of electrochemistry in an IB chemistry course

This study investigated the effectiveness of incorporating several new instructional strategies into an International Baccalaureate (IB) chemistry course in terms of how they supported high school seniors’ understanding of electrochemistry. The three new methods used were (a) providing opportunities for visualization of particle movement by student manipulation of physical models and interactive computer simulations, (b) explicitly addressing common misconceptions identified in the literature, and (c) teaching an algorithmic, step-wise approach for determining the products of an aqueous solution electrolysis. Changes in student understanding were assessed through test scores on both internally and externally administered exams over a two-year period. It was found that visualization practice and explicit misconception instruction improved student understanding, but the effect was more apparent in the short-term. The data suggested that instruction time spent on algorithm practice was insufficient to cause significant test score improvement. There was, however, a substantial increase in the percentage of the experimental group students who chose to answer an optional electrochemistry-related external exam question, indicating an increase in student confidence. Implications for future instruction are discussed.

Towards an Open Source Framework for Collaborative Problem-Based Learning Environments

This paper presents our research works in the domain of Collaborative Environments centred on Problem Based Learning (PBL) and taking advantage of existing Electronic Documents. We first present the modelling and engineering problems that we want to address; then we discuss technological issues of such a research particularly the use of OpenUSS and of the Enterprise Java Open Source Architecture (EJOSA) to implement such collaborative PBL environments.

The Future of Ubiquitous Learning

This book explores emerging pedagogical perspectives based on the design of new learning spaces supported by digital technologies and brings together some of the best research in this field. The book is divided into three themes: foundations of emerging pedagogies, learning designs for emerging pedagogies and, adaptive and personalized learning. The chapters provide up-to-date information about new pedagogical proposals, and examples for acquiring the requisite skills to both design and support learning opportunities that improve the potential of available technologies.

Precision of fit of implant-supported screw-retained 10-unit computer-aided-designed and computer-aided-manufactured frameworks made from zirconium dioxide and titanium: an in vitro study

OBJECTIVE To analyze the precision of fit of implant-supported screw-retained computer-aided-designed and computer-aided-manufactured (CAD/CAM) zirconium dioxide (ZrO) frameworks. MATERIALS AND METHODS Computer-aided-designed and computer-aided-manufactured ZrO frameworks (NobelProcera) for a screw-retained 10-unit implant-supported reconstruction on six implants (FDI positions 15, 13, 11, 21, 23, 25) were fabricated using a laser (ZrO-L, N = 6) and a mechanical scanner (ZrO-M, N = 5) for digitizing the implant platform and the cuspid-supporting framework resin pattern. Laser-scanned CAD/CAM titanium (TIT-L, N = 6) and cast CoCrW-alloy frameworks (Cast, N = 5) fabricated on the same model and designed similar to the ZrO frameworks were the control. The one-screw test (implant 25 screw-retained) was applied to assess the vertical microgap between implant and framework platform with a scanning electron microscope. The mean microgap was calculated from approximal and buccal values. Statistical comparison was performed with non-parametric tests. RESULTS No statistically significant pairwise difference was observed between the relative effects of vertical microgap between ZrO-L (median 14 μm; 95% CI 10-26 μm), ZrO-M (18 μm; 12-27 μm) and TIT-L (15 μm; 6-18 μm), whereas the values of Cast (236 μm; 181-301 μm) were significantly higher (P < 0.001) than the three CAD/CAM groups. A monotonous trend of increasing values from implant 23 to 15 was observed in all groups (ZrO-L, ZrO-M and Cast P < 0.001, TIT-L P = 0.044). CONCLUSIONS Optical and tactile scanners with CAD/CAM technology allow for the fabrication of highly accurate long-span screw-retained ZrO implant-reconstructions. Titanium frameworks showed the most consistent precision. Fit of the cast alloy frameworks was clinically inacceptable.

Individual Video Training iVT - Development of a National Infrastructure for Video-Supported Learning

Introduction: Video‐Supported Learning is particularly effective when it comes to skills and behaviors. Video registration of patient‐physician interviews, class room instruction or practical skills allow it to learners themselves, their peers, and their tutors to assess the quality of the learner's performance, to give specific feedback, and to make suggestions for improvement. Methods: In Switzerland, four pedagogical universities and two medical faculties joined to initiate the development of a national infrastructure for Video Supported Learning. The goal was to have a system that is simple to use, has most steps automated, provides the videos over the Internet, and has a sophisticated access control. Together with SWITCH, the national IT‐Support‐Organisation for Swiss Universities, the program iVT (Individual Video Training) was developed by integrating two preexisting technologies. The first technology is SWITCHcast, a podcast system. With SWITCHcast, videos are automatically uploaded to a server as soon as the registration is over. There the videos are processed and converted to different formats. The second technology is the national Single Logon System AAI (Authentification and Authorization Infrastructure) that enables iVT to link each video with the corresponding learner. The learner starts the registration with his Single Logon. Thus, the video can unambiguously be assigned. Via his institution's Learning Management System (LMS), the learner can access his video and give access to his video to peers and tutors. Results: iVT is now used at all involved institutions. The system works flawlessly. In Bern, we use iVT for the communications skills training in the forth and sixth year. Since students meet with patient actors alone, iVT is also used to certify attendance. Students are encouraged to watch the videos of the interview and the feedback of the patient actor. The offer to discuss a video with a tutor was not used by the students. Discussion: We plan to expand the use of iVT by making peer assessment compulsory. To support this, annotation capabilities are currently added to iVT. We also want to use iVT in training of practical skills, again for self as well as for peer assessment.  At present, we use iVT for quality control of patient actor's performance.

Cerebellar mechanisms for motor learning: Testing predictions from a large-scale computer simulation

The cerebellum is the major brain structure that contributes to our ability to improve movements through learning and experience. We have combined computer simulations with behavioral and lesion studies to investigate how modification of synaptic strength at two different sites within the cerebellum contributes to a simple form of motor learning—Pavlovian conditioning of the eyelid response. These studies are based on the wealth of knowledge about the intrinsic circuitry and physiology of the cerebellum and the straightforward manner in which this circuitry is engaged during eyelid conditioning. Thus, our simulations are constrained by the well-characterized synaptic organization of the cerebellum and further, the activity of cerebellar inputs during simulated eyelid conditioning is based on existing recording data. These simulations have allowed us to make two important predictions regarding the mechanisms underlying cerebellar function, which we have tested and confirmed with behavioral studies. The first prediction describes the mechanisms by which one of the sites of synaptic modification, the granule to Purkinje cell synapses (gr → Pkj) of the cerebellar cortex, could generate two time-dependent properties of eyelid conditioning—response timing and the ISI function. An empirical test of this prediction using small, electrolytic lesions of the cerebellar cortex revealed the pattern of results predicted by the simulations. The second prediction made by the simulations is that modification of synaptic strength at the other site of plasticity, the mossy fiber to deep nuclei synapses (mf → nuc), is under the control of Purkinje cell activity. The analysis predicts that this property should confer mf → nuc synapses with resistance to extinction. Thus, while extinction processes erase plasticity at the first site, residual plasticity at mf → nuc synapses remains. The residual plasticity at the mf → nuc site confers the cerebellum with the capability for rapid relearning long after the learned behavior has been extinguished. We confirmed this prediction using a lesion technique that reversibly disconnected the cerebellar cortex at various stages during extinction and reacquisition of eyelid responses. The results of these studies represent significant progress toward a complete understanding of how the cerebellum contributes to motor learning. ^

How Blended Learning Reduce Underachievement in Higher Education: An Experience in Teaching Computer Sciences.

This paper presents a blended learning approach and a study evaluating instruction in a software engineering-related course unit as part of an undergraduate engineering degree program in computing. In the past, the course unit had a lecture-based format. In view of student underachievement and the high course unit dropout rate, a distance-learning system was deployed, where students were allowed to choose between a distance-learning approach driven by a moderate constructivist instructional model or a blended-learning approach. The results of this experience are presented, with the aim of showing the effectiveness of the teaching/learning system deployed compared to the lecture-based system previously in place. The grades earned by students under the new system, following the distance-learning and blended-learning courses, are compared statistically to the grades attained in earlier years in the traditional face-to-face classroom (lecture-based) learning.

New Methodology for Integrating Teams into Multidisciplinary Project Based Learning

This paper describes the collaboration among students and professors in four different subjects, to develop multidisciplinary projects. The objective is to simulate the conditions in a company environment. A new methodology based on student interaction and content development in a Wiki environment has been developed. The collaborative server created an ‘out of the classroom’ discussion forum for students of different subjects, and allowed them to compile a ‘project work’ portfolio. Students and professors participated with enthusiasm, due to the correct well-distributed work and the easiness of use of the selected platform in which only an internet connected computer is needed to create and to discuss the multidisciplinary projects. Quality of developed projects has been dramatically improved due to integration of results provided from the different teams.

Integrated learning of computer applications for production engineering

A high productivity rate in Engineering is related to an efficient management of the flow of the large quantities of information and associated decision making activities that are consubstantial to the Engineering processes both in design and production contexts. Dealing with such problems from an integrated point of view and mimicking real scenarios is not given much attention in Engineering degrees. In the context of Engineering Education, there are a number of courses designed for developing specific competencies, as required by the academic curricula, but not that many in which integration competencies are the main target. In this paper, a course devoted to that aim is discussed. The course is taught in a Marine Engineering degree but the philosophy could be used in any Engineering field. All the lessons are given in a computer room in which every student can use each all the treated software applications. The first part of the course is dedicated to Project Management: the students acquire skills in defining, using Ms-PROJECT, the work breakdown structure (WBS), and the organization breakdown structure (OBS) in Engineering projects, through a series of examples of increasing complexity, ending up with the case of vessel construction. The second part of the course is dedicated to the use of a database manager, Ms-ACCESS, for managing production related information. A series of increasing complexity examples is treated ending up with the management of the pipe database of a real vessel. This database consists of a few thousand of pipes, for which a production timing frame is defined, which connects this part of the course with the first one. Finally, the third part of the course is devoted to the work with FORAN, an Engineering Production package of widespread use in the shipbuilding industry. With this package, the frames and plates where all the outfitting will be carried out are defined through cooperative work by the studens, working simultaneously in the same 3D model. In the paper, specific details about the learning process are given. Surveys have been posed to the students in order to get feed-back from their experience as well as to assess their satisfaction with the learning process. Results from these surveys are discussed in the paper

E-learning systems support of collaborative agreements: a theoretical model

This paper introduces a theoretical model for developing integrated degree programmes through e-learning systems as stipulated by a collaboration agreement signed by two universities. We have analysed several collaboration agreements between universities at the national, European, and transatlantic level as well as various e-learning frameworks. A conceptual model, a business model, and the architecture design are presented as part of the theoretical model. The paper presents a way of implementing e-learning systems as a tool to support inter-institutional degree collaborations, from the signing of the collaborative agreement to the implementation of the necessary services. In order to show how the theory can be tested one sample scenario is presented.

Co-evolutionary and Reinforcement Learning Techniques Applied to Computer Go players

The objective of this thesis is model some processes from the nature as evolution and co-evolution, and proposing some techniques that can ensure that these learning process really happens and useful to solve some complex problems as Go game. The Go game is ancient and very complex game with simple rules which still is a challenge for the Artificial Intelligence. This dissertation cover some approaches that were applied to solve this problem, proposing solve this problem using competitive and cooperative co-evolutionary learning methods and other techniques proposed by the author. To study, implement and prove these methods were used some neural networks structures, a framework free available and coded many programs. The techniques proposed were coded by the author, performed many experiments to find the best configuration to ensure that co-evolution is progressing and discussed the results. Using co-evolutionary learning processes can be observed some pathologies which could impact co-evolution progress. In this dissertation is introduced some techniques to solve pathologies as loss of gradients, cycling dynamics and forgetting. According to some authors, one solution to solve these co-evolution pathologies is introduce more diversity in populations that are evolving. In this thesis is proposed some techniques to introduce more diversity and some diversity measurements for neural networks structures to monitor diversity during co-evolution. The genotype diversity evolved were analyzed in terms of its impact to global fitness of the strategies evolved and their generalization. Additionally, it was introduced a memory mechanism in the network neural structures to reinforce some strategies in the genes of the neurons evolved with the intention that some good strategies learned are not forgotten. In this dissertation is presented some works from other authors in which cooperative and competitive co-evolution has been applied. The Go board size used in this thesis was 9x9, but can be easily escalated to more bigger boards.The author believe that programs coded and techniques introduced in this dissertation can be used for other domains.

Problem-based learning supported by semantic techniques

Problem-based learning has been applied over the last three decades to a diverse range of learning environments. In this educational approach, different problems are posed to the learners so that they can develop different solutions while learning about the problem domain. When applied to conceptual modelling, and particularly to Qualitative Reasoning, the solutions to problems are models that represent the behaviour of a dynamic system. The learner?s task then is to bridge the gap between their initial model, as their first attempt to represent the system, and the target models that provide solutions to that problem. We propose the use of semantic technologies and resources to help in bridging that gap by providing links to terminology and formal definitions, and matching techniques to allow learners to benefit from existing models.

E-MIS validity applied to TELMA enhanced learning environment

Enhanced learning environments are arising with great success within the field of cognitive skills training in minimally invasive surgery (MIS) because they provides multiple benefits since they avoid time, spatial and cost constraints. TELMA [1,2] is a new technology enhanced learning platform that promotes collaborative and ubiquitous training of surgeons. This platform is based on four main modules: an authoring tool, a learning content and knowledge management system, an evaluation module and a professional network. TELMA has been designed and developed focused on the user; therefore it is necessary to carry out a user validation as final stage of the development. For this purpose, e-MIS validity [3] has been defined. This validation includes usability, contents and functionality validities both for the development and production stages of any e-Learning web platform. Using e-MIS validity, the e-Learning is fully validated since it includes subjective and objective metrics. The purpose of this study is to specify and apply a set of objective and subjective metrics using e-MIS validity to test usability, contents and functionality of TELMA environment within the development stage.